JP2020507866A - Data processing method and device - Google Patents

Abstract

Embodiments of the present application provide a data processing method and device. This method distributes leaf node data pre-stored in a blockchain node to servers in a server cluster, and a server in the server cluster checksums the distributed leaf node data. Calculating respectively, and obtaining a root checksum of the data of the blockchain nodes according to the checksum of the data of the leaf nodes calculated by the servers in the server cluster. Using the embodiments of the present application, the time taken for the data checksum calculation process can be reduced, the calculation efficiency can be improved, and the normal generation of the block and the normal operation of the block chain can be ensured.

Description

  The present application relates to the field of computer technology, and in particular, to data processing methods and devices.

  Blockchain is a new application of computer technology such as distributed data storage, point-to-point transmission, consensus mechanisms, and cryptographic algorithms, where all blockchain nodes are in the same state (including the state of the database). Need that. Therefore, when a new transaction is generated at the blockchain node (that is, when new data is generated), the new data needs to be synchronized with all the blockchain nodes, and all the blockchain nodes need to be synchronized. The node needs to validate the data.

  In current technology, the verification method used by blockchain nodes for data is typically determined through a checksum (eg, a hash value) based on a bucket tree. In one example, the data of the blockchain nodes of the fabric (an already implemented blockchain application) is stored in a Merkle tree structure, where the Merkle tree has one or more leaf nodes ( That is, a bucket). A single computing device (eg, a terminal device or server) is typically used by these blockchain nodes to obtain a checksum (eg, a hash value) of the data. For example, a computing device traverses each leaf node, ranks the data of that leaf node, splices it into a string, and calculates the checksum of that string as the checksum of the data of the corresponding leaf node. I do. The computing device then computes a root checksum of the Merkle tree (eg, a root hash value), ie, a checksum of the data of the blockchain node, based on the checksum of the data of each leaf node. The above data can be verified based on this checksum.

  However, only one computing device is used to compute the root checksum of the blockchain node's data, and each computation is completed by splicing the leaf node's data into a string, so one Or, when the accumulated data volume at a plurality of leaf nodes is very large (for example, 10 million pieces of data), it takes a long time for the one computing device to execute the above-described computing process, thereby increasing the computational efficiency. And the time to generate a block is delayed, which may hinder the normal operation of the block chain.

  It is an object of embodiments of the present application to provide a data processing method and device so as to reduce the time required for the calculation process, improve the calculation efficiency, and guarantee the normal generation of blocks and the normal operation of block chains. It is.

In order to solve the above technical problems, the embodiments of the present application are implemented as follows.
An embodiment of the present application is a data processing method,
Distributing leaf node data pre-stored in the blockchain node to servers in the server cluster, and the servers in the server cluster respectively calculating checksums of the distributed leaf node data When,
Obtaining a root checksum of the data of the blockchain node according to the checksum of the data of the leaf nodes calculated by the servers in the server cluster.

Optionally, according to the checksum of the data of the leaf nodes calculated by the servers in the server cluster, obtaining the root checksum of the data of the blockchain nodes comprises:
Receiving the root checksum of the blockchain node's data sent from the servers in the server cluster.

Optionally, according to the checksum of the data of the leaf nodes calculated by the servers in the server cluster, obtaining the root checksum of the data of the blockchain nodes comprises:
Determining a root checksum of the Merkle tree corresponding to the leaf node according to the leaf node checksum;
Specifying the root checksum of the Merkle tree as the root checksum of the data of the blockchain node.

Optionally, distributing the leaf node data pre-stored in the blockchain node to servers in the server cluster comprises:
According to the number of leaf nodes previously stored in the blockchain node, the method includes transmitting data of a preset number of leaf nodes to servers in the server cluster.

  Optionally, the checksum is a hash value.

The embodiment of the present application further relates to a data processing method,
Receiving leaf node data distributed by the blockchain node;
Calculating a checksum of the data of the distributed leaf nodes to obtain a root checksum of the data of the blockchain nodes.

Optionally, after receiving the data of the leaf nodes distributed by the blockchain nodes, the method comprises:
Distributing leaf node data to preset sub-leaf nodes according to the amount of leaf node data;
Calculating a checksum of the data of each sub-leaf node;
Calculating the checksum of the data of the distributed leaf nodes comprises:
Calculating a checksum of the data of the distributed leaf nodes according to a checksum of the data of each sub-leaf node.

Optionally, distributing the leaf node data among the preset sub-leaf nodes according to the leaf node data volume comprises:
Sorting the data of the leaf nodes, sequentially selecting a predetermined number of data from the sorted data, and arranging the data on the sub-leaf node, and setting a corresponding sub-node identifier for the sub-leaf node And steps,
According to the checksum of the data of each sub-leaf node, calculating the checksum of the data of the distributed leaf nodes comprises:
Calculating a checksum of the data of the distributed leaf nodes according to a subnode identifier of the subleaf node and a checksum of each of the subleaf nodes.

Optionally, calculating a checksum of the data of the distributed leaf nodes to obtain a root checksum of the data of the blockchain node,
Calculates the checksum of the data of the distributed leaf nodes and sends the checksum of the data of the distributed leaf nodes to the blockchain node, which blocks according to the checksum of the data of the leaf nodes. Calculating the root checksum of the data of the chain node, or calculating the checksum of the data of the distributed leaf nodes, and calculating the checksum of the data of the blockchain node based on the data checksum of the distributed leaf nodes. Obtaining the root checksum and sending the root checksum to the blockchain node.

An embodiment of the present application is a data processing device,
Distributing leaf node data pre-stored in the blockchain node to servers in the server cluster so that the servers in the server cluster each calculate a checksum of the distributed leaf node data. A data distribution module configured in
A root checksum obtaining module configured to obtain a root checksum of the data of the blockchain node according to the checksum of the data of the leaf nodes calculated by the servers in the server cluster. Provide a processing device.

  Optionally, the root checksum obtaining module is configured to receive a root checksum of the data of the blockchain node transmitted from the servers in the server cluster.

  Optionally, the root checksum obtaining module determines a root checksum of the Merkle tree corresponding to the leaf node according to the checksum of the leaf node, and converts the root checksum of the Merkle tree into a blockchain. -It is configured to be specified as the root checksum of the data of the node.

  Optionally, the data distribution module sends data of a preset number of leaf nodes to the servers in the server cluster according to the number of leaf nodes pre-stored in the blockchain node. Be composed.

  Optionally, the checksum is a hash value.

An embodiment of the present application is further a data processing device,
A data receiving module configured to receive leaf node data distributed by the blockchain node;
A checksum obtaining module configured to calculate a checksum of the data of the distributed leaf nodes to obtain a root checksum of the data of the blockchain nodes.

Optionally, this device
A data distribution module configured to distribute the leaf node data to preset sub-leaf nodes according to the leaf node data amount;
A calculation module configured to calculate a checksum of the data of each sub-leaf node;
The checksum obtaining module is configured to calculate the checksum of the data of the distributed leaf nodes according to the checksum of the data of each sub-leaf node.

  Optionally, the data distribution module sorts the data of the leaf nodes, sequentially selects a predetermined number of data from the sorted data, places the data on the sub-leaf nodes, and, for the sub-leaf nodes, The checksum obtaining module is configured to set a subnode identifier, and is configured to calculate a checksum of the data of the distributed leaf nodes according to the subnode identifiers of the subleaf nodes and the respective checksums of the subleaf nodes. Is done.

  Optionally, the checksum obtaining module calculates a checksum of the data of the distributed leaf nodes and sends the checksum of the data of the distributed leaf nodes to the blockchain node, where the blockchain node It is configured to calculate the root checksum of the data of the blockchain node according to the checksum of the data of the leaf nodes, or calculate the checksum of the data of the distributed leaf nodes and calculate the checksum of the distributed leaf nodes. It is configured to obtain a root checksum of the data of the blockchain node based on the checksum of the data, and to transmit the root checksum to the blockchain node.

  From the above technical solution provided by the embodiment of the present application, in the embodiment of the present application, the data of the leaf node pre-stored in the blockchain node is distributed to the servers in the server cluster, and the server Cause the servers in the cluster to calculate the checksum of the data of the distributed leaf nodes, respectively, and then follow the checksum of the data of the leaf nodes calculated by the servers in the server cluster; It can be seen that the root checksum of the data is further obtained. In this manner, the data is distributed to the server cluster because the leaf node data is distributed to the server cluster and then the checksum of the distributed leaf node data is calculated by each server in the server cluster. In this way, the checksums of the leaf node data can be calculated in parallel, thereby reducing the time required for the calculation process, improving the calculation efficiency, and ensuring the correct generation of the blocks and the correct operation of the block chain. Can be guaranteed.

  In order to more clearly describe the technical solutions or the state of the art in the embodiments of the present application, the accompanying drawings used in the description of the embodiments or the state of the art will be briefly described below. Apparently, the accompanying drawings described below are merely some embodiments of the present application. Based on these accompanying drawings, those skilled in the art can obtain other relevant drawings without creative efforts.

This is a data processing method according to the present application. FIG. 2 is a schematic diagram illustrating data processing logic according to the present application. 4 is another data processing method according to some embodiments of the present application. 9 is yet another data processing method according to some embodiments of the present application. 1 is a schematic structural diagram showing a data processing system according to the present application. 9 is yet another data processing method according to some embodiments of the present application. 9 is yet another data processing method according to some embodiments of the present application. FIG. 4 is a schematic structural diagram showing another data processing system according to the present application. 3 is a data processing device according to some embodiments of the present application. 9 is another data processing device according to some embodiments of the present application.

  Embodiments of the present application provide a data processing method and device.

  In order that those skilled in the art can more fully understand the technical solution of the present application, the technical solutions in the embodiments of the present application will be described below clearly and completely with reference to the accompanying drawings in the embodiments of the present application. explain. Apparently, the described embodiments are merely a part rather than all of the embodiments of the present application. All other embodiments that can be obtained by a person of ordinary skill in the art based on these embodiments of the present application without creative efforts shall fall within the scope of the present application.

First Embodiment As shown in FIG. 1, an embodiment of the present application provides a data processing method. The entity that performs this method is a blockchain node. The method may include the following steps.

  In step S101, the data of the leaf node pre-stored in the blockchain node is distributed to a plurality of servers in the server cluster, and those servers in the server cluster are assigned to the distributed leaf nodes. Calculate the checksum of each data.

  Here, leaf nodes may not have subnodes. A blockchain node typically includes one or more leaf nodes (ie, buckets), each leaf node storing a certain amount of data (eg, which may be transactional data). . For the data amount of each data stored in the leaf node, a corresponding numerical value can be set. For example, the data amount of each data is in the range of 100 KB to 5 MB, and is 1 MB in one example. A server cluster may be a group composed of a plurality of the same or different servers and may be able to provide services corresponding to one or more transactions. The checksum may be a string (eg, a number or code) used to verify a file or data. In an exemplary application, the checksum may be a numerical value derived from a calculation using a checking algorithm based on data summarization or the like. Check algorithms based on data summarization may include cyclic redundancy check algorithms, message digest algorithms, secure hash algorithms, and the like.

In an implementation, the blockchain may be a decentralized distributed database, also referred to as a distributed ledger. Based on the blockchain technology, a distributed network including a large number of information recording memories (for example, terminal devices or servers) is required. Propagation of each new transaction can use a distributed network, and according to the peer-to-peer (P2P) network layer protocol, information related to the transaction is networked by individual blockchain nodes. To all other blockchain nodes directly to ensure that the data stored in all blockchain nodes in the distributed network is consistent. When a blockchain node records a new transaction, it needs to synchronize the data of the recorded new transaction with other blockchain nodes, while the other blockchain nodes You also need to verify the data. An exemplary verification process may be as follows.
A blockchain node includes one or more leaf nodes, and the data in the blockchain node is distributed among those leaf nodes. Here, all data in the leaf node includes the reception time stamp, and the order of the transactions can be determined according to the time stamp. During verification, a blockchain node may first obtain a leaf node pre-stored within the blockchain node. A corresponding node identifier, such as 5 or A8 (e.g., 5 or A8) so that it can quickly determine what leaf nodes are stored in the blockchain node and quickly determine the number of those leaf nodes A node ID (identification information)) can be set for each leaf node when the leaf node is generated. When obtaining a leaf node, a corresponding leaf node can be searched by a node identifier recorded in advance, and data stored in each leaf node can be obtained.

  Since the amount of data stored may vary due to factors such as different periods and / or different regions, the amount of data stored in one or more leaf nodes may be compared. While increasing in size, the volume of data in some other leaf nodes may be relatively small. Thus, there may be an imbalance in the amount of data stored at the leaf nodes of the blockchain node. The data in the leaf nodes is distributed to multiple processors in the server cluster to avoid affecting the generation of blocks and to reduce the time required to calculate the checksum of the leaf node data. And spread the computational load across the server cluster to improve computational efficiency.

  After obtaining the data of all the leaf nodes, the blockchain node can distribute the data of the leaf nodes to the servers in the server cluster in units of the leaf nodes. For example, the number of servers in a server cluster may be equal to the number of leaf nodes, in which case the blockchain node sends data for one leaf node to each server in the server cluster. Thus, each server in the server cluster can only contain data for one leaf node. In addition to the distribution methods described above, multiple distribution schemes can be used. For example, the leaf nodes and the data of the leaf nodes are transmitted to the servers in the server cluster in a random distribution manner. In this way, different servers may receive the same number of leaf nodes or different numbers of leaf nodes. As another example, leaf node data may be distributed according to the amount of leaf node data. In one example, a blockchain node may count the amount of data at each leaf node and then evenly distribute the leaf node's data to servers in a server cluster. For example, if there are six leaf nodes each having a data amount of 50 MB, 20 MB, 30 MB, 40 MB, 10 MB, and 10 MB, the data of the leaf node having a data amount of 50 MB is stored in the server cluster. The data is transmitted to the first server, the leaf node having the data amount of 20 MB and the data of the leaf node having the data amount of 30 MB are transmitted to the second server in the server cluster, and the data amount is 40 MB. The data of the leaf node, the leaf node having the data amount of 10 MB, and the data of the leaf node having the data amount of 10 MB may be transmitted to the third server in the server cluster.

  After receiving the distributed data of the leaf nodes, the server can calculate the checksum of the received data of each leaf node. For example, the server uses a message digest algorithm (eg, the MD5 algorithm) to calculate the MD5 value of the leaf node's received data. If one server receives the data of two leaf nodes, that is, the data of leaf node 1 and the data of leaf node 2, the server determines the MD5 value of the data of leaf node 1, and the leaf node. By calculating the MD5 value of the second data, a checksum of the received data of each leaf node can be obtained.

  In step S102, a root checksum of the data of the blockchain node is further obtained according to the checksum of the data of the leaf node calculated by the servers in the server cluster.

  In an implementation, after the servers in the server cluster calculate the checksum of the leaf node data, each server sends the checksum of the leaf node data calculated by the server to the blockchain node. can do. After the blockchain node receives the checksum of the data of all leaf nodes stored in the blockchain node, the blockchain node returns the checksum of the data of all leaf nodes based on the checksum of the data of all leaf nodes. Thus, the root checksum (ie, state) of the data in the blockchain node can be calculated. Here, when the blockchain node calculates the root checksum of the data in the blockchain node, a plurality of intermediate nodes are placed between the leaf node and the root node corresponding to the root checksum. Can be provided. As shown in FIG. 2, A, B, C, and D are leaf nodes, and A1, A2, A3,..., Ap, B1, B2, B3,..., Bq, C1, C2, C3,. Cr, and D1, D2, D3,..., Dk each represent data. As an example, assuming that the checksum is a hash value, the hash value of leaf node A is hash (A1A2A3... Ap), the hash value of leaf node B is hash (B1B2B3. The hash value of node C is hash (C1C2C3... Cr), and the hash value of leaf node D is hash (D1D2D3... Dk). M and N are intermediate nodes, so the hash value of leaf node M is hash (AB) and the hash value of leaf node N is hash (CD). In this case, the root checksum of the root node is hash (MN). By comparing the resulting root checksum of the data in the blockchain node with the above root checksum calculated by the blockchain node sending the new transaction data, the blockchain node , It can be verified that the new transaction data is valid. If the new transaction data is valid, the blockchain node can record data associated with the transaction, and if the new transaction data is not valid, the blockchain node Recording data associated with the transaction may be refused.

  Note that the root checksum calculation process described above may be completed by the server cluster. In one example, a management server or a management server cluster can be provided in the server cluster, and the management server or the management server cluster can regulate and control other servers in the server cluster. Other servers in the server cluster may calculate the checksum of the leaf node data and then send the checksum of the leaf node data to the management server or management server cluster, respectively. The management server or management server cluster can calculate the root checksum of the data in the blockchain node using the calculation method described above. The management server or management server cluster can send the obtained root checksum of the data in the blockchain node to the blockchain node, and the blockchain node receives the root checksum . The blockchain node can then perform verification via this root checksum. For details, reference can be made to the related contents described above, and thus the details will not be described here.

  In this way, the checksum of the data of the leaf node in the blockchain node is obtained by parallel calculation by a plurality of servers in the server cluster, and the calculation of the root checksum of the data in the blockchain node is performed. Improve the efficiency of data checksum calculation by decoupling from processing by one machine.

  An embodiment of the present application is a data processing method, in which data of a leaf node pre-stored in a blockchain node is distributed to servers in a server cluster, and the leaf in the server cluster is distributed. Calculating each of the checksums of the data of the nodes and further obtaining the root checksum of the data within the blockchain nodes according to the checksum of the data of the leaf nodes calculated by the servers in the server cluster; And a data processing method including: In this manner, the data is distributed to the server cluster because the leaf node data is distributed to the server cluster and then the checksum of the distributed leaf node data is calculated by each server in the server cluster. In this way, the checksums of the leaf node data can be calculated in parallel, thereby reducing the time required for the calculation process, improving the calculation efficiency, and ensuring the correct generation of the blocks and the correct operation of the block chain. Can be guaranteed.

  As shown in FIG. 3, the embodiment of the present application provides a data processing method. The entity performing the method may be a server cluster, which may include multiple servers, and each server may calculate a data checksum. The method may include the following steps.

  In step S301, data of leaf nodes distributed by the blockchain node is received.

  In an implementation, when the data in the blockchain node needs to be verified, the blockchain node obtains the data of the leaf nodes stored in the blockchain node, and in units of leaf nodes, Leaf node data can be distributed to servers in a server cluster. For a detailed distribution method and distribution process, the contents related to the above-described step S101 may be referred to, and thus the details will not be described here. The servers in the server cluster can each receive the data of the leaf nodes distributed by the blockchain node. For details, see the relevant contents of step S101 described above. It will not be described in detail.

  In step S302, the checksum of the data of the distributed leaf nodes is calculated to obtain the root checksum of the data in the blockchain node.

  In an implementation, the servers in the server cluster may calculate a checksum of the data of each received leaf node. After the calculation is completed, the servers in the server cluster can send the obtained checksums of the leaf node data to the blockchain nodes, respectively. The blockchain node can further calculate a root checksum of the blockchain node's data based on the checksum of the leaf node's data returned from the server. Since the details related to the above-described step S102 may be referred to, the details will not be described here.

  In some other embodiments of the present application, the root checksum of the blockchain node's data may be calculated by the server cluster. As described above, the management server or the management server cluster is provided in the server cluster, and the calculation of the calculated checksum of the data of each leaf node is collectively executed to route the data of the blockchain node. -A checksum can also be obtained. Since the details related to the above-described step S102 may be referred to, the details will not be described here.

  An embodiment of the present application is a data processing method, in which data of a leaf node pre-stored in a blockchain node is distributed to servers in a server cluster, and the leaf in the server cluster is distributed. Calculating each of the checksums of the data of the nodes and further obtaining the root checksum of the data within the blockchain nodes according to the checksum of the data of the leaf nodes calculated by the servers in the server cluster; And a data processing method including: In this manner, the data is distributed to the server cluster because the leaf node data is distributed to the server cluster and then the checksum of the distributed leaf node data is calculated by each server in the server cluster. In this way, the checksums of the leaf node data can be calculated in parallel, thereby reducing the time required for the calculation process, improving the calculation efficiency, and ensuring the correct generation of the blocks and the correct operation of the block chain. Can be guaranteed.

Second Embodiment As shown in FIG. 4, the embodiment of the present application provides a data processing method. This data processing method may be performed cooperatively by blockchain nodes and server clusters. The embodiment of the present application will be described in detail by taking a case where the checksum is a hash value as an example. Other forms of checksums may be performed with reference to relevant content of the embodiments of the present application, but will not be described in detail here. The method may include the following steps.

  In step S401, according to the number of leaf nodes stored in advance, the blockchain node transmits data of a preset number of leaf nodes to each of the servers in the server cluster.

  Here, the preset number can be set according to an actual situation, such as 5, 10, but will not be described in detail in the embodiment of the present application.

  In implementations, when verifying transaction data, the Merkle Tree design mechanism is often used for blockchain node data to improve verification efficiency and reduce resource consumption. In order to greatly improve the calculation efficiency of the checksum of the data of the blockchain node without changing the existing design mechanism of the blockchain data in the embodiment of the present application, the blockchain node of the embodiment of the present application is required. The data can still use the Merkle tree design mechanism. A Merkle tree may include multiple leaf nodes (ie, buckets), and the node identifiers of all leaf nodes in the Merkle tree may be recorded in blockchain nodes. When transaction data needs to be verified, the node identifiers of all leaf nodes in the Merkle tree can be obtained.

  As shown in FIG. 5, the blockchain node can obtain data of all leaf nodes based on the node identifiers of all leaf nodes, respectively, and can store leaf data stored in the blockchain node. The number of nodes and the number of servers in a server cluster can also be obtained. Depending on the number of servers and the number of leaf nodes, the blockchain node can determine the number of leaf nodes to be distributed to each server. For example, there are a total of 10 leaf nodes, and the server cluster has a total of 10 servers. In this case, the data of one leaf node can be sent to each server, or the data of a group of two or five leaf nodes can be sent to one server in the server cluster. it can.

  In the process where the blockchain node distributes leaf node data to the server cluster, the blockchain node may also distribute the leaf node identifier to the servers in the server cluster. According to the distributed node identifier, the server can send a data acquisition instruction including the node identifier to the blockchain node. Upon receiving the data acquisition instruction, the blockchain node can extract the node identifier in the data acquisition instruction, search for the data of the corresponding leaf node by the node identifier, and transmit the data to the corresponding server. . In this way, the server cluster can derive data of a plurality of corresponding leaf nodes from data of one corresponding leaf node.

  Note that in an exemplary application, leaf node data may be distributed among servers in a server cluster according to the amount of data in the leaf nodes, or may be randomly distributed among servers in a server cluster. Note that it can also be done. Since the details can be referred to the contents related to step S101 of the first embodiment, they will not be described in detail here.

  In step S402, the server cluster calculates a checksum of the data of the distributed leaf nodes.

  In step S403, the server cluster sends the checksum of the data of the distributed leaf nodes to the blockchain node.

  For the detailed processes of the above steps S402 and S403, the relevant contents of the first embodiment may be referred to, and thus the detailed description will not be given here.

  In step S404, the blockchain node determines the root checksum of the Merkle tree corresponding to the leaf node according to the above checksum of the leaf node.

  In an implementation, after receiving the checksum of the leaf nodes sent from the servers in the server cluster, the blockchain node may build a corresponding Merkle tree through those leaf nodes. Although the hash values of the leaf nodes on the Merkle tree have already been determined, the hash value of the root node of the Merkle tree (ie, the root checksum of the Merkle tree) has not yet been obtained, so these By calculating the hash value of the Merkle tree corresponding to the leaf nodes upward from the hash value of the leaf node, the root checksum of the Merkle tree corresponding to these leaf nodes can be obtained.

  In step S405, the blockchain node specifies the root checksum of the Merkle tree as the root checksum of the data of the blockchain node.

  In an exemplary application, the root checksum may also be calculated by the server cluster, the process comprising calculating the checksum of the data of the distributed leaf nodes and the data of the distributed leaf nodes. May include obtaining a root checksum of the blockchain node's data based on the checksum of the blockchain node and sending the root checksum to the blockchain node. Since a detailed process can be referred to the relevant contents of the first embodiment, it will not be described in detail here.

  An embodiment of the present application is a data processing method, in which data of a leaf node pre-stored in a blockchain node is distributed to servers in a server cluster, and the leaf in the server cluster is distributed. Calculating each of the checksums of the data of the nodes and further obtaining the root checksum of the data within the blockchain nodes according to the checksum of the data of the leaf nodes calculated by the servers in the server cluster; And a data processing method including: In this manner, the data is distributed to the server cluster because the leaf node data is distributed to the server cluster and then the checksum of the distributed leaf node data is calculated by each server in the server cluster. In this way, the checksums of the leaf node data can be calculated in parallel, thereby reducing the time required for the calculation process, improving the calculation efficiency, and ensuring the correct generation of the blocks and the correct operation of the block chain. Can be guaranteed.

Third Embodiment As shown in FIG. 6, the embodiment of the present application provides a data processing method. This data processing method may be performed cooperatively by blockchain nodes and server clusters. The embodiment of the present application will be described in detail by taking a case where the checksum is a hash value as an example. Other forms of checksums may be performed with reference to relevant content of the embodiments of the present application, but will not be described in detail here. The method may include the following steps.

  In step S601, the blockchain node distributes pre-stored leaf node data to servers in the server cluster.

  The detailed process of step S601 may be referred to the contents related to the first embodiment and the second embodiment, and will not be described in detail here.

  In step S602, the server cluster distributes the data of the leaf nodes to preset sub-leaf nodes according to the data amount of the leaf nodes.

  Here, there is no related relationship such as an belonging relationship, a dependent relationship, a parent relationship, or a child relationship between the subleaf node and the leaf node. A sub-leaf node may be a data packet containing one or more data, and a leaf node (bucket) may be a container in a Merkle tree for storing data. The number of sub-leaf nodes may be greater than the number of leaf nodes. For example, if the number of leaf nodes is 5, the number of sub-leaf nodes may be 20.

  In an implementation, one or more of the leaf nodes pre-stored in the blockchain node may have a large amount of data (eg, contain one million data). Thus, when distributing the leaf node data to the servers in the server cluster and calculating the hash value of the leaf node, the server splices a large amount of data in the leaf node and splices the data. Then, the hash value of the spliced character string is calculated. This process still takes a long time and the resource consumption by the server is still high. In view of this, a plurality of sub-leaf nodes can be preset, or the maximum amount of data that each sub-leaf node can accommodate, eg, 1 GB or 500 MB, can be set as -Can also be set on nodes. The data of the leaf nodes can be distributed to a plurality of preset sub-leaf nodes by a random distribution method or a uniform distribution method.

  There may be various ways to perform step S602. The following provides an optional processing method. This processing method corresponds to sorting of leaf node data, selecting a predetermined number of data in order from the sorted data, and arranging them in sub-leaf nodes, respectively. Setting the sub-node identifier to be performed.

  According to the data processing speed and checksum calculation speed of each server in the server cluster, and according to the number of servers in the server cluster, the server cluster has a high overall data processing efficiency (eg, a set efficiency threshold). It is possible to determine the amount of data that each server can process while ensuring higher data processing efficiency), and then determine the amount or number of data that each sub-leaf node can accommodate. . The server cluster may calculate the total amount of leaf node data distributed to each server. In this case, the server cluster sorts the data of the distributed leaf nodes according to the time stamp indicating the time at which the data was stored in the blockchain node, and sets a preset one of the sorted data. Several pieces of data are sequentially distributed to each sub-leaf node, a corresponding sub-node identifier is set for each of the sub-leaf nodes according to the order of the data, and the data position of the sub-leaf node in the data of all the sub-leaf nodes is determined. As shown.

  For example, when 50 pieces of data each having 5 MB are stored in sub-leaf nodes distributed by servers in the server cluster, the data amount is 250 MB. If the amount of data that each sub-leaf node can accommodate is 25 MB, then 250/25 = 10, so 10 sub-leaf nodes are obtained. In this case, the subleaf nodes are numbered 1 to 10 as subnode identifiers according to the order of data. After the above processing, the storage locations of the 50 data are as follows. That is, the first to fifth data are sequentially stored in the sub-leaf node of No. 1, the sixth to tenth data are sequentially stored in the sub-leaf node of No. 2, The data is stored in the sub-leaf node of No. 3 in order, and then stored in the same manner to obtain the storage position of each data. Since each data is 5 MB, each sub-leaf node can contain 5 data.

  In step S603, the server cluster calculates a checksum of the data of each sub-leaf node.

  In an implementation, after the servers in the server cluster obtain the corresponding subleaf nodes, they obtain the data stored in those subleaf nodes, and then use each of the pre-configured inspection algorithms to The checksum of the sub-leaf node can be calculated. For example, sort the data stored at the sub-leaf node, and then use SHA256 (secure hash algorithm 256) on the sorted data to determine the SHA256 value (ie, hash value) as the checksum of the sub-leaf node. You can also calculate.

  In step S604, the server cluster calculates the checksum of the data of the distributed leaf nodes according to the checksum of the data of each sub-leaf node.

  In an implementation, after the server cluster obtains the checksum of each subleaf node, the checksums of those subleaf nodes can be sorted according to the order of the subnode identifiers. The server cluster then performs a computation based on the checksum of the sub-leaf nodes intensively using a preset inspection algorithm to obtain the checksum of the corresponding leaf node, thereby obtaining the blockchain A checksum of the data of the leaf nodes distributed by the nodes can be obtained.

  For example, based on the example of step S602, the hash value of each of the data of the ten sub-leaf nodes can be obtained by the processing of step S603. Since the data of the ten sub-leaf nodes is distributed from the data of one leaf node, the aggregation execution calculation shown in FIG. 2 is executed for the obtained hash value of the data of the ten sub-leaf nodes. Thus, the hash value of the corresponding leaf node can be obtained.

  It should be noted that the sub-leaf node data can also be obtained in a pull-type manner by the set sub-node identifier of the sub-leaf node. Accordingly, the processing in step S604 may be as follows. That is, the checksum of the data of the distributed leaf nodes is calculated according to the subnode identifier of the subleaf node and the checksum of each subleaf node. For the detailed processing, it is sufficient to refer to the related contents described above, and therefore, the details will not be described here.

  In step S605, the server cluster sends the distributed checksum of the leaf node to the blockchain node.

  In step S606, the blockchain node determines the root checksum of the Merkle tree corresponding to the leaf node according to the checksum of the leaf node.

  In an implementation, the root checksum of the data of the blockchain node may be calculated using a preset check algorithm based on the checksum of the leaf node. For example, according to the location of the leaf node corresponding to the recorded node identifier in all leaf nodes of the blockchain node, such as ABCF, ABE, and AD, etc. A node distribution tree (i.e., a Merkle tree) composed of leaf nodes can be obtained. When the checksums of the leaf nodes (ie, the checksums of B + C + D + E + F) are obtained, the root checksum of the Merkle tree is calculated according to the checksums of the leaf nodes, thereby obtaining the root of the data of the blockchain node. -A checksum can be obtained.

  In step S607, the blockchain node specifies the root checksum of the Merkle tree as the root checksum of the data of the blockchain node.

  For the detailed processes of step S605 and step S607, the contents related to the first embodiment and the second embodiment may be referred to, and thus the detailed description will not be provided here.

  An embodiment of the present application is a data processing method, wherein the node identifiers of leaf nodes are distributed to server clusters, and the server cluster obtains the obtained amount of data stored at the leaf nodes of the target blockchain. Distributing each predetermined number of data among the sub-leaf nodes, and then calculating the checksum of each sub-leaf node, and determining the checksum of the corresponding leaf node, according to Finally, providing a checksum of the leaf nodes to the blockchain node and calculating a checksum of the blockchain node's data. In this manner, the server cluster redistributes the data stored on the leaf nodes to obtain subleaf nodes, and then calculates the checksum of the subleaf nodes so that the data is evenly distributed to the compute server cluster. By performing the checksum parallel calculation in a distributed manner, the time required for the calculation process is reduced, the calculation efficiency is improved, and the normal generation of the block and the normal operation of the block chain are guaranteed.

Fourth Embodiment As shown in FIG. 7, the embodiment of the present application provides a data processing method. This data processing method may be performed cooperatively by blockchain nodes and server clusters. Here, the server cluster may further include a first server cluster and a second server cluster as shown in FIG. FIG. 8 shows a data processing system. The data processing system may include two levels of server clusters, a first server cluster and a second server cluster. Here, the first server cluster is at a lower level than the blockchain node, and the second server cluster is at a lower level than the first server cluster. This hierarchical structure can achieve data re-combination, data distribution, etc., and accelerate data processing speed. The embodiment of the present application will be described in detail by taking a case where the checksum is a hash value as an example. Other forms of checksums may be performed with reference to relevant content of the embodiments of the present application, but will not be described in detail here. The method may include the following steps.

  In step S701, the blockchain node obtains a node identifier of a pre-stored leaf node.

  In an implementation, when data is stored in a blockchain node, a leaf node is generated in the blockchain node and a node identifier of the leaf node is also generated. Thus, a blockchain may include multiple leaf nodes, each leaf node storing a certain amount of data. Once the node identifier is generated, the node identifier can be stored and the position of the leaf node corresponding to that node identifier among all leaf nodes in the blockchain node can be recorded. For example, the generated node identifier is F, and the location of the leaf node corresponding to the node identifier may be ABCF.

  In step S702, the blockchain node sends the node identifier to a server in the server cluster.

  In an implementation, based on the system structure shown in FIG. 8, a blockchain node can obtain data stored in leaf nodes included in the blockchain node, and according to a pre-developed distribution rule, Or, randomly, the node identifiers of those leaf nodes can be divided into one or more groups. Each group of node identifiers can be sent to one server in the first server cluster.

  In step S703, the first server cluster obtains the data of the leaf nodes corresponding to the node identifiers from the blockchain nodes according to the distributed node identifiers.

  In an implementation, the servers in the first server cluster send data acquisition instructions including the node identifiers to the blockchain devices, and then copy the leaf node data corresponding to those node identifiers to the blockchain nodes. Can be taken from

  In step S704, the first server cluster generates one or more sub-leaf nodes according to the obtained data amount of the leaf nodes.

  Here, as described above, in the embodiment of the present application, there is no related relationship such as an belonging relationship, a dependent relationship, a parent relationship, or a child relationship between the sub-leaf node and the leaf node. A sub-leaf node may be a data packet containing one or more data, and a leaf node (bucket) may be a container in a Merkle tree for storing data.

  In an implementation, the amount of data or the number of data that can be accommodated by the sub-leaf node may be preset, such as 100 MB or 10 for example. The total amount of leaf node data distributed to each server of the first server cluster can be calculated, one or more depending on the amount or number of data each sub-leaf node can accommodate. Multiple sub-leaf nodes can be created.

  In step S705, the first server cluster sorts the data of the leaf nodes, sequentially selects a predetermined number of data from the sorted data, and arranges the data in the corresponding sub-leaf nodes. Set corresponding subnode identifiers for those subleaf nodes.

  In an implementation, the amount of time required for any server in the first server cluster to calculate the hash value of one or more data can be pre-tested in an iterative test manner, where Thus, the number of data corresponding to the relatively short time length and the relatively low server processing load can be selected. This number may be set as a preset number, for example, 30 or 50. Since each data has a timestamp in the process of storage or blockchain transaction, the time of storage or transaction of each data can be determined through this timestamp. Thus, the time stamp of each data can be obtained, and a plurality of data can be sorted according to the order of the time stamps. A predetermined number of data can be sequentially selected from the sorted plurality of data and distributed to the corresponding sub-leaf nodes. To label the order of the distributed data of different subleaf nodes, a subnode identifier can be set for the corresponding subleaf node based on the distributed data.

  For example, the preset number of data may be three, and the leaf node data may include A, B, C, D, E, F, G, H, and K. After sorting the data according to the timestamp, the order of the above data may be HGFFEDCBAK. In this case, three data HGF are distributed to one sub-leaf node, three data EDC are distributed to one sub-leaf node, and three data BAK are distributed. It can be distributed over one subleaf node. To label the order of the data stored in these three subleaf nodes, the subnode identifier of the subleaf node where HGF is located is set to subnode 1 and EDC is located. The subnode identifier of the subleaf node may be set as subnode2, and the subnode identifier of the subleaf node where BAK is located may be set as subnode3.

  In step S706, the first server cluster distributes the data of the sub-leaf node to the servers in the second server cluster.

  In implementations, indicator data such as the current remaining bandwidth and / or data rate of each server in the second server cluster may be obtained, respectively. The computing capacity of each server of the first server cluster can be evaluated based on the obtained index data, and according to the magnitude of the computing capacity, the data of the corresponding sub-leaf node is transferred to the second server cluster. Can be sent to servers in the cluster.

  Further, the number of sub-leaf nodes distributed to the servers in the second server cluster may be adjusted in order to improve the computation efficiency as much as possible. In one example, indicator data such as the current remaining bandwidth and / or data rate of each server in the second server cluster can be obtained, respectively. The computing power of each server can be evaluated based on the obtained index data, and the corresponding sub-leaf nodes are distributed to the servers in the second server cluster according to the magnitude of the computing power. Can be. For example, a second server cluster may include five servers, with each server distributing two subleaf nodes. If a server in the second server cluster is determined by computation to have the strongest computing power, data for three of the ten sub-leaf nodes is transferred to this server. Can be sent. If one server in the second server cluster is determined by the calculation to have the weakest computing power, the data of one of the ten subleaf nodes is sent to this server. can do. In this way, the generated one or more sub-leaf nodes can be provided to servers in the second server cluster in a balanced manner.

  In step S707, the second server cluster calculates a hash value of each sub-leaf node and feeds back the hash value to the corresponding server in the first server cluster.

  In an implementation, after the server of the second server cluster receives the corresponding subleaf node, the server extracts the data of each subleaf node and sorts the data according to the order of the time stamp of the data. be able to. The server can obtain a character string composed of the sorted data and calculate a hash value of the character string, that is, a hash value of the sub-leaf node, using a preset hash algorithm. In this way, the second server cluster can obtain a hash value for each subleaf node, and then use that hash value via the corresponding server to the corresponding server in the first server cluster. Can be sent to

  In step S708, the first server cluster updates the hash values of the distributed leaf nodes according to the hash values of the subleaf nodes transmitted from the second server cluster and the subnode identifiers of those subleaf nodes. decide.

  In an implementation, the servers in the first server cluster may each obtain a subnode identifier for each subleaf node after receiving the checksum of the subleaf nodes returned from the second server cluster. . These servers can then sort the subleaf nodes according to the subnode identifier of each subleaf node, collect the hash values of the sorted subleaf nodes, and obtain the hash values of the subleaf nodes. For example, the order of the hash values of the sub-leaf nodes may be determined according to the order of the sub-leaf nodes, and the sorted hash values may form a character string. The hash value of the character string can be calculated using a preset hash algorithm, and this hash value becomes the hash value of the corresponding leaf node. In addition, other hash value calculation schemes may be used to determine the hash value of a leaf node. For example, the average of the hash values of one or more sub-leaf nodes can be calculated as the hash value of the leaf node, or the hash value of the leaf node can be calculated as the weight of each sub-leaf node and each sub-leaf node. -It can also be obtained based on the hash value of the node.

  In step S709, the first server cluster sends the hash value of the distributed leaf node to the blockchain node.

  In step S710, the blockchain node determines the root checksum of the Merkle tree corresponding to the leaf node according to the checksum of the leaf node, and determines the root checksum of the Merkle tree as the blockchain. Specify as the root checksum of the node's data.

  An embodiment of the present application is a data processing method, wherein one or a plurality of sub-leaf nodes in which a predetermined number of data are distributed according to an amount of data of a leaf node of a blockchain node are generated. And then distributing these sub-leaf nodes to a second server cluster to calculate the checksum of each sub-leaf node, and the checksum of the corresponding leaf node according to the checksum of each sub-leaf node And finally providing the checksums of these leaf nodes to the blockchain node and calculating a root checksum of the blockchain node's data. provide. Thus, the first server cluster redistributes the data stored in the leaf nodes to obtain subleaf nodes, and distributes the subleaf nodes to the second server cluster to calculate the checksum. Reduce the time required for the computation process, improve computational efficiency, achieve normal block generation and block by performing parallel checksum computations so that data is evenly distributed across the second server cluster. Ensure the normal operation of the chain.

Fifth Embodiment The above is the data processing method provided by the embodiment of the present application. Based on the same concept, embodiments of the present application further provide a data processing device as shown in FIG.

The data processing device may be a blockchain node provided in the above embodiments, and in one example, may be a terminal device (eg, a personal computer) or a server. The device may include a data distribution module 901 and a root checksum acquisition module 902, where:
The data distribution module 901 distributes the data of the leaf nodes pre-stored in the blockchain node to the servers in the server cluster, and checksums the data of the leaf nodes to which the servers in the server cluster are distributed. Are configured to calculate
The root checksum acquisition module 902 is configured to further obtain a root checksum of the data of the blockchain node according to the checksum of the data of the leaf nodes calculated by the servers in the server cluster.

  In an embodiment of the present application, the root checksum obtaining module 902 is configured to receive a root checksum of data of a blockchain node transmitted from a server in the server cluster.

  In an embodiment of the present application, the root checksum obtaining module 902 determines the root checksum of the Merkle tree corresponding to the leaf node according to the checksum of the leaf node, and determines the root checksum of the Merkle tree. As the root checksum of the blockchain node's data.

  In the embodiment of the present application, the data distribution module 901 transmits data of a preset number of leaf nodes to servers in a server cluster according to the number of leaf nodes pre-stored in the blockchain node. It is configured as follows.

  In the embodiment of the present application, the checksum is a hash value.

  An embodiment of the present application is a data processing device, in which leaf node data pre-stored in a blockchain node is distributed to servers in a server cluster, and the servers in the server cluster are distributed. Calculating the checksums of the data of the leaf nodes respectively and further obtaining the root checksum of the data of the blockchain nodes according to the checksum of the data of the leaf nodes calculated by the servers in the server cluster. A data processing device configured as described above. In this manner, the data is distributed to the server cluster because the leaf node data is distributed to the server cluster and then the checksum of the distributed leaf node data is calculated by each server in the server cluster. In this way, the checksums of the leaf node data can be calculated in parallel, thereby reducing the time required for the calculation process, improving the calculation efficiency, and ensuring the correct generation of the blocks and the correct operation of the block chain. Can be guaranteed.

Sixth Embodiment Based on the same concept, embodiments of the present application further provide a data processing device as shown in FIG.

The data processing device may be a server cluster provided in the above embodiment, and the device may include a data receiving module 1001 and a checksum obtaining module 1002, where:
The data receiving module 1001 is configured to receive data of leaf nodes distributed by blockchain nodes,
The checksum acquisition module 1002 is configured to calculate a checksum of the distributed leaf node data and obtain a root checksum of the blockchain node data.

In an embodiment of the present application, the device is:
A data distribution module configured to distribute the leaf node data to preset sub-leaf nodes according to the leaf node data amount;
A calculation module configured to calculate a checksum of the data of each sub-leaf node;
Accordingly, the checksum acquisition module 1002 is configured to calculate the checksum of the data of the distributed leaf nodes according to the checksum of the data of each sub-leaf node.

In the embodiment of the present application, the data distribution module sorts the data of the leaf nodes, sequentially selects a predetermined number of data from the sorted data, arranges the data in the sub-leaf nodes, respectively, Configured to set a corresponding subnode identifier for the node,
Accordingly, the checksum acquisition module 1002 is configured to calculate a checksum of the data of the distributed leaf nodes according to the subnode identifiers of the subleaf nodes and the checksum of each subleaf node.

  In an embodiment of the present application, the checksum acquisition module 1002 calculates the checksum of the data of the distributed leaf node, transmits the checksum of the data of the distributed leaf node to the blockchain node, and The chain node is configured to calculate the root checksum of the data of the blockchain node according to the checksum of the data of the leaf nodes, or calculate the checksum of the data of the distributed leaf nodes; It is configured to obtain a root checksum of data of the blockchain node based on the checksum of data of the distributed leaf nodes, and to transmit the root checksum to the blockchain node.

  An embodiment of the present application is a data processing device, which distributes data of a leaf node pre-stored in a blockchain node to servers in a server cluster, and the servers in the server cluster are distributed. Calculating the checksums of the data of the leaf nodes respectively and further obtaining the root checksum of the data of the blockchain nodes according to the checksum of the data of the leaf nodes calculated by the servers in the server cluster. A data processing device configured as described above. In this manner, the data is distributed to the server cluster because the leaf node data is distributed to the server cluster and then the checksum of the distributed leaf node data is calculated by each server in the server cluster. In this way, the checksums of the leaf node data can be calculated in parallel, thereby reducing the time required for the calculation process, improving the calculation efficiency, and ensuring the correct generation of the blocks and the correct operation of the block chain. Can be guaranteed.

  In the 1990's, improvements in technology can be clearly distinguished from improvements in hardware (eg, improvements in circuit structures, such as diodes, transistors, switches, etc.), or in software (improvements in method flow). However, with the development of technology, many of the current improvements in method flow may be considered as direct improvements to the hardware circuit structure. In most cases, the designer obtains the corresponding hardware circuit structure by programming the improved method flow into the hardware circuit. Therefore, it cannot be concluded that a refinement of the method flow cannot be realized by a hardware module. For example, a programmable logic device (PLD) (eg, a field programmable gate array (FPGA)) is an integrated circuit whose logical function is determined by a user programming the device. Designers need to program themselves to "integrate" the digital system into one PLD and not have to ask chip manufacturers to design and manufacture dedicated IC chips. At present, moreover, this kind of programming is mostly implemented by "logic compiler" software, rather than manually manufacturing IC chips. Logic compiler software is similar to the software compiler used to develop and write programs, but uses a specific programming language called Hardware Description Language (HDL) to write source code before compiling. Must be used. HDL is not only one 1, ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java (registered trademark) Hardware Description Language), Lava , Lola, MyHDL, PALASM, and RHDL (Ruby Hardware Description Language). Currently most commonly used are VHDL (Very-High-Speed Integrated Circuit Hardware Description Language) and Verilog. It is very easy for a person skilled in the art to obtain a hardware circuit, perform some logic programming on the method flow using the above HDL, and implement the logic method flow by programming the method flow into an IC. You should also notice.

  The controller can be implemented in any suitable manner. For example, the controller may be in the form of, for example, a microprocessor or processor, or (micro) processors, logic gates, switches, application specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers. May be in the form of a computer readable medium that stores computer readable program code (eg, software or firmware) that can be executed by a computer. Examples of control devices include, but are not limited to, microcontrollers such as 625D manufactured by ARC, AT91SAM manufactured by Atmel, PIC18F26K20 manufactured by Microchip, and C8051F320 manufactured by Silicon Labs. The memory controller may also be implemented as part of the control logic of the memory. Those skilled in the art will recognize that the controller is not only implemented by purely computer readable program code, but also performs logic programming for the steps of the method so that the controller performs the same functions as logic gates, switches, ASICs, programmable logic. It should also be noted that implementation in the form of a controller, an embedded microcontroller, etc. is entirely possible. Therefore, such a control device is sometimes regarded as a hardware component. However, a device included in the control device and configured to realize various functions includes an internal structure of the hardware component. May be considered. Alternatively, devices configured to perform various functions may be considered both as software modules that perform the method and as internal structures of hardware components.

  The systems, devices, modules, or units described in the above embodiments can be implemented by computer chips or entities, or can be implemented by functional products. A typical mounting device is a computer. In one example, the computer may be, for example, a personal computer, a laptop computer, a mobile phone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet console, and the like. It can be a computer, a wearable device, or a combination of any of these devices.

  For convenience of description, the above devices are divided into various units according to the function of the description. The functions of these units may be implemented in one or more software and / or hardware when practicing the present application.

  One of ordinary skill in the art will appreciate that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may be implemented as an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may be implemented on one or more computer-usable storage media (including, but not limited to, magnetic disk memory, CD-ROM, optical memory, etc.) containing computer-usable program code. Computer program product.

  The invention has been described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the invention. It is understood that computer program instructions may also be used to implement each of the processes and / or blocks in these flow diagrams and / or block diagrams, and combinations of the processes and / or blocks in these flow diagrams and / or block diagrams. I want to be. These computer program instructions are provided to a general purpose computer, special purpose computer, embedded processor, or other processor of a programmable data processing device to create a machine, and the instructions are executed by a computer or other programmable data processing device. When executed by the processor of the device, an apparatus may be generated that performs the functions specified in one or more processes in the flowcharts and / or one or more blocks in the block diagrams.

  Storing these computer program instructions in a computer readable memory that can instruct a computer or other programmable data processing device to operate in a particular manner, wherein the instructions stored in the computer readable memory are stored in an instruction device. Can also be produced. The instruction device performs the functions specified in one or more processes in the flowcharts and / or one or more blocks in the block diagrams.

  These computer program instructions may also be loaded into a computer or other programmable data processing device to generate a computer-implemented process by causing a series of operating steps to be performed on the computer or other programmable device. . Accordingly, instructions executing on a computer or other programmable device provide steps to perform a function specified in one or more processes in a flowchart and / or one or more blocks in a block diagram. .

  In a typical configuration, a computing device includes one or more processors (CPUs), an input / output interface, a network interface, and memory.

  The memory may include computer readable media such as volatile memory, random access memory (RAM), and / or non-volatile memory, for example, read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

  Computer-readable media includes persistent media, volatile media, movable media, and non-transitory media that can store information by any method or technique. The information may be computer readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change random access memory (PRAM), static random access memory (PRAM), which can be used to store information accessible to a computing device. Access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read only memory (ROM), electrically erasable programmable read only memory (EEPROM) Flash memory or other memory technology, compact disk read only memory (CD-ROM), digital versatile disk (DVD) or other optical memory, cassette, cassette and disk memory or other magnetic memory device, or other Any of Such as a non-transmission medium. Computer-readable media, as defined herein, does not include transitory media such as modulated data signals and carriers.

  Further, the term "comprising" or "comprising" or other variants of these terms, is intended to include non-exclusive inclusion, thereby making a process, method, or article comprising a series of elements. Or that the device not only includes those elements, but also includes other elements not explicitly listed, or further includes elements specific to the process, method, article, or device. I want to. Unless further constrained, the definition of each element by the phrase "comprising one" does not exclude that the process, method, article, or device that includes the element further includes the same type of element. .

  Those skilled in the art will appreciate that embodiments of the present application may be provided as a method, system, or computer program product. Thus, the present application may be implemented as an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. In addition, the present application may be implemented on one or more computer-usable storage media (including, but not limited to, magnetic disk memory, CD-ROM, optical memory, etc.) containing computer-usable program code. It may also be in the form of a computer program product.

  This application may be described in the context of computer-executable instructions, such as program modules, being executed by computers. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform particular tasks or implement particular abstract data types. The present application may be implemented in a distributed computing environment. In such a distributed computing environment, remote processing devices connected via a communications network perform tasks. In a distributed computing environment, program modules may be located in local and remote computer storage media, such as storage devices.

  The embodiments of the present application are described progressively in each embodiment by focusing on the differences from the other embodiments, and these embodiments will refer to each other for the same or similar parts. be able to. In particular, embodiments of the system have been described relatively briefly, since embodiments of the system are substantially similar to embodiments of the method. For the relevant portions, the description of the embodiment of the method may be referred to.

  The above is only an embodiment of the present application and is not used to limit the present application. For those skilled in the art, the present application may have various modifications and alterations. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present application shall be included in the claims of the present application.

Claims (18)

A data processing method,
Distributing leaf node data pre-stored in a blockchain node to servers in a server cluster, wherein the server in the server cluster checksums the data of the distributed leaf nodes. Calculating each; and
Obtaining a root checksum of the data of the blockchain node according to the checksum of the data of the leaf node calculated by the servers in the server cluster. Obtaining the root checksum of the data of the blockchain node according to the checksum of the data of the leaf node calculated by the server in the server cluster;
The method of claim 1, comprising receiving the root checksum of the data of the blockchain node transmitted from the server in the server cluster. Obtaining the root checksum of the data of the blockchain node according to the checksum of the data of the leaf node calculated by the server in the server cluster;
Determining a root checksum of a Merkle tree corresponding to the leaf node according to the checksum of the leaf node;
Specifying the root checksum of the Merkle tree as the root checksum of the data of the blockchain node. Distributing the leaf node data pre-stored in the blockchain node to servers in the server cluster,
2. The method according to claim 1, further comprising transmitting data of a preset number of leaf nodes to servers in the server cluster according to the number of the leaf nodes pre-stored in the blockchain node. The described method.   The method according to claim 1, wherein the checksum is a hash value. A data processing method,
Receiving leaf node data distributed by the blockchain node;
Calculating a checksum of the data of the distributed leaf nodes to obtain a root checksum of the data of the blockchain nodes. After said step of receiving leaf node data distributed by blockchain nodes,
Distributing the data of the leaf nodes to preset sub-leaf nodes according to the amount of data of the leaf nodes;
Calculating a checksum of the data of each sub-leaf node;
Calculating the checksum of the data of the distributed leaf nodes,
7. The method of claim 6, comprising calculating the checksum of the data of the distributed leaf nodes according to the checksum of the data of each sub-leaf node. According to the amount of data of the leaf node, the step of distributing the data of the leaf node to preset sub-leaf nodes,
Sorting the data of the leaf nodes;
Selecting a predetermined number of data in order from the sorted data and arranging them in the sub-leaf node;
Setting a corresponding subnode identifier for the subleaf node;
Calculating the checksum of the data of the distributed leaf nodes according to the checksum of the data of each sub-leaf node,
The method of claim 7, comprising calculating the checksum of the data of the distributed leaf nodes according to the subnode identifier of the subleaf node and the checksum of each of the subleaf nodes. Calculating the checksum of the data of the distributed leaf nodes to obtain a root checksum of the data of the blockchain node;
Calculating the checksum of the data of the distributed leaf nodes and transmitting the checksum of the data of the distributed leaf nodes to the blockchain node, wherein the blockchain node Calculating the root checksum of the data of the blockchain node according to the checksum of the data of a node, or calculating the checksum of the data of the distributed leaf nodes, and Obtaining the root checksum of the data of the blockchain node based on the checksum of the data of a leaf node, and transmitting the root checksum to the blockchain node. 7. The method according to 6. A data processing device,
Distributing leaf node data pre-stored in a blockchain node to servers in a server cluster, wherein the server in the server cluster checksums the data of the distributed leaf nodes. A data distribution module configured to calculate each;
A root checksum obtaining module configured to obtain a root checksum of the data of the blockchain node according to the checksum of the data of the leaf node calculated by the server in the server cluster; A data processing device comprising:   The method of claim 10, wherein the root checksum obtaining module is configured to receive the root checksum of the data of the blockchain node transmitted from the server in the server cluster. device.   The root checksum obtaining module determines a root checksum of a Merkle tree corresponding to the leaf node according to the checksum of the leaf node, and calculates the root checksum of the Merkle tree: The device of claim 10, configured to designate as the root checksum of the data of the blockchain node.   The data distribution module transmits data of a preset number of leaf nodes to servers in the server cluster according to the number of the leaf nodes pre-stored in the blockchain node. The device of claim 10, wherein the device is configured.   The device according to any one of claims 10 to 13, wherein the checksum is a hash value. A data processing device,
A data receiving module configured to receive leaf node data distributed by the blockchain node;
A checksum obtaining module configured to calculate a checksum of the data of the distributed leaf nodes to obtain a root checksum of the data of the blockchain nodes. A data distribution module configured to distribute the data of the leaf nodes to preset sub-leaf nodes according to a data amount of the leaf nodes;
A calculation module configured to calculate a checksum of the data of each sub-leaf node;
16. The device of claim 15, wherein the checksum obtaining module is configured to calculate the checksum of the data of the distributed leaf nodes according to the checksum of the data of each sub-leaf node. The data distribution module sorts the data of the leaf nodes, selects a predetermined number of data in order from the sorted data, arranges the data in the sub-leaf node, and for the sub-leaf node, Configured to set a corresponding subnode identifier,
The checksum obtaining module is configured to calculate the checksum of the data of the distributed leaf nodes according to the subnode identifier of the subleaf node and the checksum of each of the subleaf nodes. 17. The device of claim 16, wherein: The checksum obtaining module calculates the checksum of the data of the distributed leaf nodes and sends the checksum of the data of the distributed leaf nodes to the blockchain node, A chain node configured to calculate the root checksum of the data of the blockchain node according to the checksum of the data of the leaf node, or the data of the distributed leaf nodes Calculating the checksum of the data of the distributed leaf nodes, obtaining the root checksum of the data of the blockchain node based on the checksum of the data of the distributed leaf nodes, and converting the root checksum to the blockchain. Configured to send to nodes The device of claim 15, wherein